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Use what you know to convert.35 km/hr to m/min. Graphing in Physics.

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Presentation on theme: "Use what you know to convert.35 km/hr to m/min. Graphing in Physics."— Presentation transcript:

1 Use what you know to convert.35 km/hr to m/min

2 Graphing in Physics

3 Graphing A way to display data that is collected in an experiment. They must be constructed accurately and neatly so data is understood. Three main types of graphs: line, pie and bar.

4 4 parts of a graph 1.Title & Axis labels 2.Independent variable 3.Dependent variable 4.Scales for variable

5 Parts of the Graph Title- –A statement placed above the graph to help explain the graph. Axis labels –give units and description of data on each axis (side) of graph A graph is incomplete if the title and axis labels are missing.

6 Parts of a Graph The Independent Variable- –The ONE thing in the experiment that is controlled by the experimenter. –It usually concerns time, depth, or temperature. –It is on the horizontal or x-axis.

7 Parts of a Graph Dependent Variable –is the variable that is directly affected by the changes in the independent variable. –Examples of possible dependent variables: Student grades, salary earned, number of assignments completed –This variable is placed on the vertical or Y-axis.

8 Parts of a Graph Scales for each variable- –In order to plot a graph you must set a scale to include all the data points. –Scales will start at 0 and climb in equal intervals such as 2,5,10 etc. –The scales for the x and y axis can be different. –Set the scale so that the entire space provided is used You want the graph to be spaced out so it is easier to read and understand

9 Graphing Scientific Data Instead of connecting the points “dot-to- dot” style, draw in a line of best fit –a line that goes through most of the points, but not all of them

10 Graphing Scientific Data Lines of best fit allow for interpolation and extrapolation of the data presented Interpolation- used to approximate values that are between data points on the graph Extrapolation- used to approximate values beyond the range of the data


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